Quantifying the Kinetics of Signaling and Arrestin Recruitment by Nervous System G-Protein Coupled Receptors.

Neurons integrate inputs over different time and space scales. Fast excitatory synapses at boutons (ms and µm), and slow modulation over entire dendritic arbors (seconds and mm) are all ultimately combined to produce behavior. Understanding the timing of signaling events mediated by G-protein-coupled receptors is necessary to elucidate the mechanism of action of therapeutics targeting the nervous system. Measuring signaling kinetics in live cells has been transformed by the adoption of fluorescent biosensors and dyes that convert biological signals into optical signals that are conveniently recorded by microscopic imaging or by fluorescence plate readers. Quantifying the timing of signaling has now become routine with the application of equations in familiar curve fitting software to estimate the rates of signaling from the waveform. Here we describe examples of the application of these methods, including (1) Kinetic analysis of opioid signaling dynamics and partial agonism measured using cAMP and arrestin biosensors; (2) Quantifying the signaling activity of illicit synthetic cannabinoid receptor agonists measured using a fluorescent membrane potential dye; (3) Demonstration of multiplicity of arrestin functions from analysis of biosensor waveforms and quantification of the rates of these processes. These examples show how temporal analysis provides additional dimensions to enhance the understanding of GPCR signaling and therapeutic mechanisms in the nervous system.

Analyzing kinetic signaling data for G-protein-coupled receptors.

In classical pharmacology, bioassay data are fit to general equations (e.g. the dose response equation) to determine empirical drug parameters (e.g. EC50 and Emax), which are then used to calculate chemical parameters such as affinity and efficacy. Here we used a similar approach for kinetic, time course signaling data, to allow empirical and chemical definition of signaling by G-protein-coupled receptors in kinetic terms. Experimental data are analyzed using general time course equations (model-free approach) and mechanistic model equations (mechanistic approach) in the commonly-used curve-fitting program, GraphPad Prism. A literature survey indicated signaling time course data usually conform to one of four curve shapes: the straight line, association exponential curve, rise-and-fall to zero curve, and rise-and-fall to steady-state curve. In the model-free approach, the initial rate of signaling is quantified and this is done by curve-fitting to the whole time course, avoiding the need to select the linear part of the curve. It is shown that the four shapes are consistent with a mechanistic model of signaling, based on enzyme kinetics, with the shape defined by the regulation of signaling mechanisms (e.g. receptor desensitization, signal degradation). Signaling efficacy is the initial rate of signaling by agonist-occupied receptor (kτ), simply the rate of signal generation before it becomes affected by regulation mechanisms, measurable using the model-free analysis. Regulation of signaling parameters such as the receptor desensitization rate constant can be estimated if the mechanism is known. This study extends the empirical and mechanistic approach used in classical pharmacology to kinetic signaling data, facilitating optimization of new therapeutics in kinetic terms.

A kinetic method for measuring agonist efficacy and ligand bias using high resolution biosensors and a kinetic data analysis framework.

The kinetics/dynamics of signaling are of increasing value for G-protein-coupled receptor therapeutic development, including spatiotemporal signaling and the kinetic context of biased agonism. Effective application of signaling kinetics to developing new therapeutics requires reliable kinetic assays and an analysis framework to extract kinetic pharmacological parameters. Here we describe a platform for measuring arrestin recruitment kinetics to GPCRs using a high quantum yield, genetically encoded fluorescent biosensor, and a data analysis framework to quantify the recruitment kinetics. The sensor enabled high temporal resolution measurement of arrestin recruitment to the angiotensin AT1 and vasopressin V2 receptors. The analysis quantified the initial rate of arrestin recruitment (kτ), a biologically-meaningful kinetic drug efficacy parameter, by fitting time course data using routine curve-fitting methods. Biased agonism was assessed by comparing kτ values for arrestin recruitment with those for Gq signaling via the AT1 receptor. The kτ ratio values were in good agreement with bias estimates from existing methods. This platform potentially improves and simplifies assessment of biased agonism because the same assay modality is used to compare pathways (potentially in the same cells), the analysis method is parsimonious and intuitive, and kinetic context is factored into the bias measurement.

Cilia have high cAMP levels that are inhibited by Sonic Hedgehog-regulated calcium dynamics.

Protein kinase A (PKA) phosphorylates Gli proteins, acting as a negative regulator of the Hedgehog pathway. PKA was recently detected within the cilium, and PKA activity specifically in cilia regulates Gli processing. Using a cilia-targeted genetically encoded sensor, we found significant basal PKA activity. Using another targeted sensor, we measured basal ciliary cAMP that is fivefold higher than whole-cell cAMP. The elevated basal ciliary cAMP level is a result of adenylyl cyclase 5 and 6 activity that depends on ciliary phosphatidylinositol (3,4,5)-trisphosphate (PIP3), not stimulatory G protein (Gαs), signaling. Sonic Hedgehog (SHH) reduces ciliary cAMP levels, inhibits ciliary PKA activity, and increases Gli1. Remarkably, SHH regulation of ciliary cAMP and downstream signals is not dependent on inhibitory G protein (Gαi/o) signaling but rather Ca2+ entry through a Gd3+-sensitive channel. Therefore, PIP3 sustains high basal cAMP that maintains PKA activity in cilia and Gli repression. SHH activates Gli by inhibiting cAMP through a G protein-independent mechanism that requires extracellular Ca2+ entry.

New DAG and cAMP Sensors Optimized for Live-Cell Assays in Automated Laboratories.

Protein-based, fluorescent biosensors power basic research on cell signaling in health and disease, but their use in automated laboratories is limited. We have now created two live-cell assays, one for diacyl glycerol and another for cAMP, that are robust (Z' > 0.7) and easily deployed on standard fluorescence plate readers. We describe the development of these assays, focusing on the parameters that were critical for optimization, in the hopes that the lessons learned can be generalized to the development of new biosensor-based assays.

Ratiometric biosensors based on dimerization-dependent fluorescent protein exchange.

We have developed a versatile new class of genetically encoded fluorescent biosensor based on reversible exchange of the heterodimeric partners of green and red dimerization-dependent fluorescent proteins. We demonstrate the use of this strategy to construct both intermolecular and intramolecular ratiometric biosensors for qualitative imaging of caspase activity, Ca(2+) concentration dynamics and other second-messenger signaling activities.

A multiplexed fluorescent assay for independent second-messenger systems: decoding GPCR activation in living cells.

There is a growing need in drug discovery and basic research to measure multiple second-messenger components of cell signaling pathways in real time and in relevant tissues and cell types. Many G-protein-coupled receptors activate the heterotrimeric protein, Gq, which in turn activates phospholipase C (PLC). PLC cleaves phosphatidylinositol 4,5-bisphosphate (PIP2) to produce two second messengers: diacylglycerol (DAG), which remains in the plasma membrane, and inositol triphosphate (IP3), which diffuses through the cytosol to release stores of intracellular calcium ions (Ca(2+)). Our goal was to create a series of multiplex sensors that would make it possible to simultaneously measure two different components of the Gq pathway in living cells. Here we describe new fluorescent sensors for DAG and PIP2 that produce robust changes in green or red fluorescence and can be combined with one another, or with existing Ca(2+) sensors, in a live-cell assay. These assays can detect multiple components of Gq signaling, simultaneously in real time, on standard fluorescent plate readers or live-cell imaging systems.

Diazoxide-unresponsive congenital hyperinsulinism in children with dominant mutations of the ß-cell sulfonylurea receptor SUR1.

OBJECTIVE: Congenital hyperinsulinemic hypoglycemia is a group of genetic disorders of insulin secretion most commonly associated with inactivating mutations of the ß-cell ATP-sensitive K(+) channel (K(ATP) channel) genes ABCC8 (SUR1) and KCNJ11 (Kir6.2). Recessive mutations of these genes cause hyperinsulinism that is unresponsive to treatment with diazoxide, a channel agonist. Dominant K(ATP) mutations have been associated with diazoxide-responsive disease. We hypothesized that some medically uncontrollable cases with only one K(ATP) mutation might have dominant, diazoxide-unresponsive disease. RESEARCH DESIGN AND METHODS: Mutations of the K(ATP) genes were identified by sequencing genomic DNA. Effects of mutations on K(ATP) channel function in vitro were studied by expression in COSm6 cells. RESULTS: In 15 families with diazoxide-unresponsive diffuse hyperinsulism, we found 17 patients with a monoallelic missense mutation of SUR1. Nine probands had de novo mutations, two had an affected sibling or parent, and four had an asymptomatic carrier parent. Of the 13 different mutations, 12 were novel. Expression of mutations revealed normal trafficking of channels but severely impaired responses to diazoxide or MgADP. Responses were significantly lower compared with nine SUR1 mutations associated with dominant, diazoxide-responsive hyperinsulinism. CONCLUSIONS: These results demonstrate that some dominant mutations of SUR1 can cause diazoxide-unresponsive hyperinsulinism. In vitro expression studies may be helpful in distinguishing such mutations from dominant mutations of SUR1 associated with diazoxide-responsive disease.